A design language for premium, dark-themed knowledge interfaces.
"Numbers are heroes, labels are whispers."
Fala Dev,
Como mencionei algumas vezes, tenho trabalhado bastante em conteúdo gratuito para complementar meus cursos.
E se você quiser aproveitar o fim de semana para aprender algo novo, aqui estão vários estudos completos e gratuitos:
| a.line.me | |
| ad.line-scdn.net | |
| api.today.line.me | |
| crs-event.line.me | |
| jp-col-tcp.nelo.linecorp.com | |
| legy.line-apps.com | |
| legy.line-apps.com.akadns.net | |
| legy-jp-addr-ds.line-apps.com | |
| linecrs.line-scdn.net | |
| sch.line.me |
| blueprint: | |
| name: Sensor Light | |
| description: > | |
| # 💡 Sensor Light | |
| **Version: 8.5** | |
| Your lighting experience, your way - take control and customize it to perfection! 💡✨ |
The OpenClaw guide and config is now maintained as a proper repository with better structure and actionable examples.
New location: https://github.com/digitalknk/openclaw-runbook
| 0.0.0.0 a-0001.a-msedge.net | |
| 0.0.0.0 a-0002.a-msedge.net | |
| 0.0.0.0 a-0003.a-msedge.net | |
| 0.0.0.0 a-0004.a-msedge.net | |
| 0.0.0.0 a-0005.a-msedge.net | |
| 0.0.0.0 a-0006.a-msedge.net | |
| 0.0.0.0 a-0007.a-msedge.net | |
| 0.0.0.0 a-0008.a-msedge.net | |
| 0.0.0.0 a-0009.a-msedge.net | |
| 0.0.0.0 a-msedge.net |
This is an OPML version of the HN Popularity Contest results for 2025, for importing into RSS feed readers.
Plug: if you want to find content related to your interests from thousands of obscure blogs and noisy sources like HN Newest, check out Scour. It's a free, personalized content feed I work on where you define your interests in your own words and it ranks content based on how closely related it is to those topics.
| FROM ubuntu | |
| RUN apt-get update | |
| RUN apt-get install -y curl | |
| RUN curl -sL https://deb.nodesource.com/setup_18.x | bash - | |
| RUN apt-get upgrade -y | |
| RUN apt-get install -y nodejs | |
| COPY package.json package.json | |
| COPY package-lock.json package-lock.json |
Last updated: November 3, 2025
This guide is about training nanochat on 2 DGX Sparks linked via QSFP/CX7. I estimate the training to take about 5 days (about half the training time on 1 DGX Spark).
Follow the following NVIDIA tutorials to link and test your Spark cluster: